Power electronics is a rapidly growing field that plays a crucial role in the efficient conversion and control of electrical energy in transport, aerospace, and energy storage applications. However, the design and optimization of power electronics can be challenging due to the complexity of the systems and the various trade-offs involved (e.g., power density, efficiency, cost). Artificial intelligence (AI) and machine learning (ML) techniques have the potential to significantly improve the design approach for power electronics converters.
This project will propose new power electronics converter optimization techniques based on artificial intelligence (AI) and machine learning (ML). The main aim is to investigate the use of AI and ML techniques for the holistic multi-objective (MO) optimization of power electronics, with a focus on magnetic components’ design, converter topology, thermal management, and cost. Another aim of the project is to evaluate the impact of AI and ML-based power electronics optimisation on power density, efficiency, and cost. To validate the developed techniques hardware prototypes will be designed and suitable benchmarking will be done against other established optimisation methods.
Applicants are invited to undertake a full-time PhD programme to investigate the design optimisation issues for high-power-density power converters. The work will begin with an extensive analysis, simulation, and modelling phase. Once successful solutions are identified, several case studies will be conducted. Finally, laboratory-based testing will begin to allow practical validation of ideas followed by implementation of the prototype test hardware in our dedicated laboratories at the power electronics and machine centre of the University of Nottingham. The project will be partially funded by CSA Catapult.
The successful candidate will be based at the Power Electronics, Machines and Control (PEMC) Group, within the Faculty of Engineering of the University of Nottingham. The group has state of the art experimental facilities for power electronics and electrical drives and is renowned for its ability to conduct pure and applied research at realistic power levels (up to 2MW continuous). Depending on how eligibility criteria are met, candidates will be entitled to full award (stipend at the UKRI rate and full tuition fees). UKRI 2023/24 rate is £18,622 per annum (tax free). A Research Training Support Grant will also be awarded towards consumables and travel for the PhD project. The successful candidate is expected to have short secondments at CSA Catapult’s R&D department situated in Newport.
Candidate requirements:
The successful candidate is expected to be highly motivated and must hold/achieve a minimum of a 2:1 Bachelor's level degree (or international equivalent) in Electrical or Electronic Engineering or a related discipline and with good knowledge of Power Electronics Converters, Semiconductor Devices, and Control. It is desirable that the candidate has good knowledge of circuit design software, programming skills (MATLAB, Simulink, C etc.) and DSP / FPGA based control.
Please contact Dr Rishad Ahmed for further information.
Email: [Email Address Removed]
How to apply
Please apply here https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx and choose ‘Power Electronics: Sustainable Electric Propulsion PhD’ as your course. Details of the course can be found below- https://www.nottingham.ac.uk/pgstudy/course/research/2022/power-electronics-sustainable-electric-propulsion-cdt-phd
The following documentation is required as part of the application:
- CV
- Covering letter explaining why you are applying for the CDT
- Degree transcripts and certificates
- If English is not your first language, a copy of your English language qualifications
When applying for this studentship, please include the title “PhD in Optimization of Power Electronics using Artificial Intelligence and Machine Learning Techniques” within the personal statement of the application.
About the CDT
The overall vision of the CDT is the creation of a new generation of UK specialists driving the electric revolution in the transport sector. As this sector is reliant on a reliable supply of low carbon electricity, development of wave energy is seen as a potentially important part of this sector.
We aim to create a new school of thinking amongst engineers and scientists, capable of leading the transformation from fossil fuel transport to sustainable and environmentally friendly electric transport.
Our partners
A collaboration between two of the UK's largest and most forward-thinking research groups in electric propulsion: the Electrical Power Group at Newcastle University and the Power Electronics, Machines and Control Research Group at the University of Nottingham.
The CDT is supported by over 30 industrial and network partners to deliver unprecedented high-quality research and comprehensive training.
Training
We have developed a radical new training programme that will equip our students with a new school of thinking for solving problems to ensure maximum research impact.
Highlights of the training programme include:
- Fusion-Training-Units - a revolutionary new training method combining technical knowledge with professional skills.
- Supervisor-on-Demand scheme - students will get support from their main academic and industrial supervisor and also from a pool of experts throughout training and research.
- A large choice of taught modules and laboratories - subjects in engineering, science, business tailored to students' needs.
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